{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from torch import nn\n",
    "import pandas as pd\n",
    "from torch.utils.data import DataLoader\n",
    "from transformer_turbine_src.transformer_dataset import TransformerDataset\n",
    "from transformer_turbine_src.model import Model\n",
    "from torch.optim import Adam\n",
    "from trainer import Trainer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "seq = 32\n",
    "d_model = 64\n",
    "train_rate = 0.8\n",
    "test_rate = 0.2\n",
    "batch_size = 128\n",
    "features = 8\n",
    "target = \"dspeed\"\n",
    "device = \"cuda\"\n",
    "source_file = \"/home/duxiangyu/data/turbine_data/data_without_features/normed_processed_data/001.csv\"\n",
    "target_file = \"/home/duxiangyu/data/turbine_data/data_without_features/normed_processed_data/002.csv\"\n",
    "source_denorm_file = \"/home/duxiangyu/data/turbine_data/data_without_features/normed_processed_data_para/001.csv\"\n",
    "target_denorm_file = \"/home/duxiangyu/data/turbine_data/data_without_features/normed_processed_data_para/002.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "source_df = pd.read_csv(source_file)\n",
    "target_df = pd.read_csv(target_file)\n",
    "\n",
    "target_idx = target_df.columns.get_loc(target)\n",
    "\n",
    "train_source = source_df[:int(train_rate * len(source_df))]\n",
    "train_target = target_df[:int(train_rate * len(target_df))]\n",
    "train_dataset = TransformerDataset(source_df=train_source, target_df=train_target, target_idx=target_idx, seq=seq, device=device)\n",
    "\n",
    "test_source = source_df[-int(test_rate * len(source_df)):]\n",
    "test_target = target_df[-int(test_rate * len(target_df)):]\n",
    "test_dataset = TransformerDataset(source_df=test_source, target_df=test_target, target_idx=target_idx, seq=seq, device=device)\n",
    "\n",
    "trainloader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True)\n",
    "testloader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Model(d_model=d_model, features=features, device=device)\n",
    "optimizer = Adam(model.parameters(), lr=5e-4)\n",
    "criterion = nn.MSELoss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainer = Trainer(model=model, criterion=criterion, optimizer=optimizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoth 0, Training loss: 0.0505865183710638\n",
      "Epoth 1, Training loss: 0.003113811580179673\n",
      "Epoth 2, Training loss: 0.003032972532997115\n"
     ]
    }
   ],
   "source": [
    "trainer.train(trainloader, epochs=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test loss 0.0014401574153453112\n"
     ]
    }
   ],
   "source": [
    "y_true = []\n",
    "y_predict = []\n",
    "loss = 0.0\n",
    "MSE = nn.MSELoss()\n",
    "for src, tgt, y in testloader:\n",
    "    y = y[:,-1]\n",
    "    y_hat = model.predict(src, tgt)\n",
    "    y_predict.extend(y_hat.tolist())\n",
    "    y_true.extend(y.tolist())\n",
    "    loss += MSE(y_hat, y)\n",
    "print(f\"test loss {loss / len(testloader)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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dnZ2oVauWGD58uLh8+bLGet9//72oUqWKsLa2FgEBAeLgwYN5rqG2x9mFEOKff/4R3bp1E87OzsLGxkbUrFlTfPnllxrrfPXVV8Lb21uYmZnlGQ7AmDG+TGZmpvD09BQAxC+//JLn/cOHD4vXX39d2NraCi8vL/HZZ5+Jffv25Xm8X9t9c//+fdGjRw9Rrlw5Ub58efHBBx+If/75R+s1i4uLE/369RMeHh7C0tJSeHt7i3feeUds3bpVvY6h9w6RqSiE0OFPBiIiIqIyhn2SiIiIiLRgkkRERESkBZMkIiIiIi2YJBERERFpwSSJiIiISAsmSURERERacDBJLbKysnDnzh04ODgYdVZ2IiIiMh0hBFJTU+Hl5QUzMyPUA8k8TpNYtGiRerC7Jk2aiOPHjxe4/qNHj8RHH30kPDw8hJWVlahevbrYs2eP+n3VQHM5l5o1a+oV082bN/PsgwsXLly4cOFSMpabN28alJPkJmtN0qZNmzBmzBgsWbIEgYGBWLBgAYKDg3H58mW4ubnlWT8jIwNvvvkm3NzcsHXrVnh7e+P69et5pkV47bXXsH//fvVrCwv9TtPBwQEAcPPmTTg6Oup/YkRERFTkUlJS4OPjo/4eLyxZk6T58+djyJAhGDhwIABgyZIl2LNnD1atWoXx48fnWX/VqlV4+PAhjhw5AktLSwCAn59fnvUsLCzg4eFhcFyqJjZHR0cmSURERCWMsbrKyNZxOyMjA6dPn0ZQUFB2MGZmCAoKyneW8l27dqFp06YYPnw43N3dUadOHcyYMQNKpVJjvatXr8LLywtVq1ZFaGhontm6iYiIiF5GtpqkBw8eQKlUwt3dXaPc3d0dly5d0rrNv//+iz/++AOhoaH45ZdfEBsbi48++ggvXrxAeHg4ACAwMBARERGoWbMm7t69iylTpqBly5b4559/8q1+S09PR3p6uvp1SkqKkc6SiIiISqoS9XRbVlYW3NzcsGzZMpibm8Pf3x+3b9/G3Llz1UnS22+/rV6/Xr16CAwMhK+vLzZv3oywsDCt+505cyamTJlSJOdAREREJYNsSZKLiwvMzc2RmJioUZ6YmJhvfyJPT09YWlrC3NxcXVa7dm0kJCQgIyMDVlZWebZxdnZGjRo1EBsbm28sEyZMwJgxY9SvVR2/XkapVOLFixcvXY+ouMv9/4qIiGRMkqysrODv74/IyEh07doVgFRTFBkZiREjRmjdpnnz5li/fj2ysrLU4x9cuXIFnp6eWhMkAEhLS0NcXBz69u2bbyzW1tawtrbWOXYhBBISEvD48WOdtyEq7pydneHh4cGxwYiI/iNrc9uYMWPQv39/BAQEoEmTJliwYAGePHmiftqtX79+8Pb2xsyZMwEAw4YNw6JFizBq1Ch8/PHHuHr1KmbMmIGRI0eq9zl27Fh06tQJvr6+uHPnDsLDw2Fubo7evXsbLW5VguTm5oZy5crxS4VKNCEEnj59inv37gGQamyJiEjmJCkkJAT379/HpEmTkJCQgAYNGmDv3r3qztw3btzQGDHTx8cH+/btwyeffIJ69erB29sbo0aNwueff65e59atW+jduzeSkpLg6uqKFi1a4NixY3B1dTVKzEqlUp0gVaxY0Sj7JJKbra0tAODevXtwc3Nj0xsREQCFEELIHURxk5KSAicnJyQnJ+cZJ+n58+eIj4+Hn5+f+ouFqDR49uwZrl27hipVqsDGxkbucIiI9FbQ97chOMGtgdjERqUN72kiIk1MkoiIiIi0YJJExYJCocCOHTvkDsMk/Pz8sGDBAvVruc518uTJaNCgQZEfl4iopGKSVMYcPXoU5ubm6Nixo97b5v6yL8n8/PygUCigUChgZ2eHRo0aYcuWLUVy7Lt372oMeloQJjZERPJhkiQTpRKIigI2bJD+zTX9nMmsXLkSH3/8MQ4ePIg7d+4UzUGLqalTp+Lu3bs4e/YsGjdujJCQEBw5ckTruhkZGUY7roeHh17jchERlSpPn8odgc6YJMlg+3bAzw9o2xZ4/33pXz8/qdyU0tLSsGnTJgwbNgwdO3ZEREREnnX+97//oXHjxrCxsYGLiwu6desGAGjTpg2uX7+OTz75RF0DA2iv6ViwYAH8/PzUr0+ePIk333wTLi4ucHJyQuvWrXHmzBmd4162bBm8vLyQlZWlUd6lSxcMGjQIABATE4O2bdvCwcEBjo6O8Pf3x6lTpwrcr4ODAzw8PFCjRg0sXrwYtra2+N///gdAqmn66quv0K9fPzg6OmLo0KEAgL/++gstW7aEra0tfHx8MHLkSDx58kS9z3v37qFTp06wtbVFlSpVsG7dujzHzd3cphq2okKFCrCzs0NAQACOHz+OiIgITJkyBTExMeprrvqdPX78GIMHD4arqyscHR3xxhtvICYmRuM4s2bNgru7OxwcHBAWFobnz5/rdsGJiExl82bpC0+P7wA5MUkqYtu3A+++C9y6pVl++7ZUbspEafPmzahVqxZq1qyJPn36YNWqVcg5AsSePXvQrVs3dOjQAWfPnkVkZCSaNGnyX9zbUalSJXXty927d3U+bmpqKvr374+//voLx44dQ/Xq1dGhQwekpqbqtP17772HpKQkHDhwQF328OFD7N27F6GhoQCA0NBQVKpUCSdPnsTp06cxfvx4WFpa6hyjhYUFLC0tNWqMvv76a9SvXx9nz57Fl19+ibi4OLRv3x49evTA33//jU2bNuGvv/7SGCF+wIABuHnzJg4cOICtW7fi+++/Vw/SqE1aWhpat26N27dvY9euXYiJicFnn32GrKwshISE4NNPP8Vrr72mvuYhISHqa3Lv3j38+uuvOH36NBo1aoR27drh4cOHAKTf9eTJkzFjxgycOnUKnp6e+P7773W+HkRERrd8ORASAty/D/TsCZSEyeQF5ZGcnCwAiOTk5DzvPXv2TFy4cEE8e/ZM7/1mZgpRqZIQgPZFoRDCx0dazxSaNWsmFixYIIQQ4sWLF8LFxUUcOHBA/X7Tpk1FaGhovtv7+vqKb775RqMsPDxc1K9fX6Psm2++Eb6+vvnuR6lUCgcHB/G///1PXQZA/Pzzz/lu06VLFzFo0CD166VLlwovLy+hVCqFEEI4ODiIiIiIfLcv6FzS09PFjBkzBACxe/du9ftdu3bV2CYsLEwMHTpUo+zQoUPCzMxMPHv2TFy+fFkAECdOnFC/f/HiRQFA47rlPNelS5cKBwcHkZSUpDVObdf30KFDwtHRUTx//lyjvFq1amLp0qVCCOl3+dFHH2m8HxgYmGdfORXm3iYieqmHD4Xw9ZW+8EJDhUhNNfohCvr+NgRrkorQoUN5a5ByEgK4eVNaz9guX76MEydOqKdnsbCwQEhICFauXKleJzo6Gu3atTP6sRMTEzFkyBBUr14dTk5OcHR0RFpaGm7cuKHzPkJDQ7Ft2zakp6cDANatW4devXqpR2QfM2YMBg8ejKCgIMyaNQtxcXEv3efnn38Oe3t7lCtXDrNnz8asWbM0OrQHBARorB8TE4OIiAjY29url+DgYGRlZSE+Ph4XL16EhYUF/P391dvUqlULzs7O+cYQHR2Nhg0bokKFCjpfi5iYGKSlpaFixYoascTHx6vP++LFiwgMDNTYrmnTpjofg4jI6MqXBzZuBFasAH76CbC3lzuil5J1WpKyRtcWKj1asnS2cuVKZGZmwsvLS10mhIC1tTUWLVoEJycng0YQNzMz02iyA4AXL15ovO7fvz+SkpKwcOFC+Pr6wtraGk2bNtWrM3SnTp0ghMCePXvQuHFjHDp0CN988436/cmTJ+P999/Hnj178OuvvyI8PBwbN25U96nSZty4cRgwYADs7e3h7u6eZzBFOzs7jddpaWn44IMPNOYKVKlcuTKuXLmi8/moGHLN09LS4OnpiaioqDzvFZSQEREVmadPgS++AD77DMg5H+Trr0tLCcGapCKk67yhxp5fNDMzEz/++CPmzZuH6Oho9RITEwMvLy9s2LABAFCvXj1ERkbmux8rKysocz2G5+rqioSEBI1EKTo6WmOdw4cPY+TIkejQoQNee+01WFtb48GDB3qdg42NDbp3745169Zhw4YNqFmzJho1aqSxTo0aNfDJJ5/gt99+Q/fu3bF69eoC9+ni4oJXXnkFHh66zXzfqFEjXLhwAa+88kqexcrKCrVq1UJmZiZOnz6t3uby5ct4/PhxvvusV68eoqOj1X2JctN2zRs1aoSEhARYWFjkicPFxQUAULt2bRw/flxju2PHjr30HImICu3CBaBxY2DBAiA0tOge3zYBJklFqGVLoFIlIL/vY4UC8PGR1jOm3bt349GjRwgLC0OdOnU0lh49eqib3MLDw7FhwwaEh4fj4sWLOHfuHGbPnq3ej5+fHw4ePIjbt2+rk5w2bdrg/v37mDNnDuLi4rB48WL8+uuvGsevXr06fvrpJ1y8eBHHjx9HaGioQTUooaGh2LNnD1atWqXusA1Ic46NGDECUVFRuH79Og4fPoyTJ0+idu3ahlyufH3++ec4cuQIRowYgejoaFy9ehU7d+5Ud9yuWbMm2rdvjw8++ADHjx/H6dOnMXjw4ALPtXfv3vDw8EDXrl1x+PBh/Pvvv9i2bRuOHj0KQLrm8fHxiI6OxoMHD5Ceno6goCA0bdoUXbt2xW+//YZr167hyJEj+OKLL9RP9I0aNQqrVq3C6tWrceXKFYSHh+P8+fNGvR5ERHlERAABAVKiBAAnTgDnzskaUqEYpWdTKWOqjttCCLFtm9RBW6HI22lboZDeN7Z33nlHdOjQQet7x48fFwBETEzMf/FtEw0aNBBWVlbCxcVFdO/eXb3u0aNHRb169YS1tbXIeev88MMPwsfHR9jZ2Yl+/fqJ6dOna3TcPnPmjAgICBA2NjaievXqYsuWLXk6geMlHbeFkDp8e3p6CgAiLi5OXZ6eni569eolfHx8hJWVlfDy8hIjRowo8HekrRO6Lu+fOHFCvPnmm8Le3l7Y2dmJevXqienTp6vfv3v3rujYsaOwtrYWlStXFj/++ONLz/XatWuiR48ewtHRUZQrV04EBASI48ePCyGEeP78uejRo4dwdnYWAMTq1auFEEKkpKSIjz/+WHh5eQlLS0vh4+MjQkNDxY0bN9T7nT59unBxcRH29vaif//+4rPPPmPHbSIyjdRUIfr10/xiq1tXiIsXizQMY3fcVgiRq0MJFTiL8PPnzxEfH1+omdK3bwdGjdLsxO3jI9VMdu9eiMCJCsEY9zYRlUHnzkmP9F+6lF02ZAiwcCFgQKtBYRT0/W0IdtyWQffuQJcu0lNsd+9KfZBatgTMzeWOjIiISEdCSE+qjRwJqAartbcHli0D/nuSuqRjkiQTc3OgTRu5oyAiIjLQkSPAf7MRAAAaNJBG1K5eXbaQjI0dt4mIiEh/zZtnJ0kffQQcPVqqEiSANUlERESkCyHyPp69YAHQuTOQYyDe0oQ1SURERFSw5GSpc/b69ZrltralNkECmCQRERFRQU6eBBo2BLZuBT74ADBgdoGSikkSERER5SWE1JzWvDkQHy+VWVgAesy7WdKxTxIRERFpevgQGDQI2Lkzu+z116UJan195YuriLEmiYiIiLIdOyY1r+VMkMaOBQ4eLFMJEsAkiYxg8uTJcHd3h0KhwI4dO+QOxyQmT56MBg0aqF8PGDAAXbt2LdQ+jbEPIiKjycoC5s6VRjdWNalVrAjs3i2VW1rKG58MmCSVEQMGDIBCoYBCoYCVlRVeeeUVTJ06FZmZmYXa78WLFzFlyhQsXboUd+/exdtvv13oWHMnJAWtpzonCwsL+Pn54ZNPPkFaWlqhY3iZhQsXIiIiQqd1r127BoVCgejoaIP3QURkco8eAfPmAarvhebNgejoUv302suwT1IZ0r59e6xevRrp6en45ZdfMHz4cFhaWmLChAl670upVEKhUCAuLg4A0KVLFyhyj59RBF577TXs378fmZmZOHz4MAYNGoSnT59i6dKledbNyMiAlZWVUY7r5ORULPZBRGQ0FSsC69YBwcHAZ58BU6dKHbXLMNYklSHW1tbw8PCAr68vhg0bhqCgIOzatQsAkJ6ejrFjx8Lb2xt2dnYIDAxEVFSUetuIiAg4Oztj165dePXVV2FtbY1BgwahU6dOAAAzMzONJGnFihWoXbs2bGxsUKtWLXz//fcasdy6dQu9e/dGhQoVYGdnh4CAABw/fhwRERGYMmUKYmJi1LVEBdW2WFhYwMPDA5UqVUJISAhCQ0PV56SqkVqxYoXGpK2PHz/G4MGD4erqCkdHR7zxxhuIiYnR2O+sWbPg7u4OBwcHhIWF4blqXqL/5G4qy8rKwpw5c/DKK6/A2toalStXxvTp0wEAVapUAQA0bNgQCoUCbf6bjyb3PtLT0zFy5Ei4ubnBxsYGLVq0wMmTJ9XvR0VFQaFQIDIyEgEBAShXrhyaNWuGy5cv53t9iIjylZUF5K55b9dOesR/xowynyABrEkq02xtbZGUlAQAGDFiBC5cuICNGzfCy8sLP//8M9q3b49z586h+n/DzD99+hSzZ8/GihUrULFiRXh6eqJNmzYYOHAg7t69q97vunXrMGnSJCxatAgNGzbE2bNnMWTIENjZ2aF///5IS0tD69at4e3tjV27dsHDwwNnzpxBVlYWQkJC8M8//2Dv3r3Yv38/AP1qXGxtbZGRkaF+HRsbi23btmH79u0w/28G4ffeew+2trb49ddf4eTkhKVLl6Jdu3a4cuUKKlSogM2bN2Py5MlYvHgxWrRogZ9++gnffvstqlatmu9xJ0yYgOXLl+Obb75BixYtcPfuXVz6b0bsEydOoEmTJti/fz9ee+21fGuzPvvsM2zbtg1r1qyBr68v5syZg+DgYMTGxqJChQrq9b744gvMmzcPrq6u+PDDDzFo0CAcPnxY52tERIR794C+fQFra6mDds6WgAI+68ocQXkkJycLACI5OTnPe8+ePRMXLlwQz549y7vhvHlCeHu/fOnUKe+2nTrptu28eQadU//+/UWXLl2EEEJkZWWJ33//XVhbW4uxY8eK69evC3Nzc3H79m2Nbdq1aycmTJgghBBi9erVAoCIjo7WWOfnn38WuW+jatWqifXr12uUffXVV6Jp06ZCCCGWLl0qHBwcRFJSktZYw8PDRf369V96TrnXO3XqlHBxcRHvvvuu+n1LS0tx79499TqHDh0Sjo6O4vnz53liXrp0qRBCiKZNm4qPPvpI4/3AwECNY+W8nikpKcLa2losX75ca5zx8fECgDh79qxGec59pKWlCUtLS7Fu3Tr1+xkZGcLLy0vMmTNHCCHEgQMHBACxf/9+9Tp79uwRALTfj3oq8N4motLjwAEhPD2FkEZCMvh7pTgq6PvbEKxJMqaUFOD27Zev5+OTt+z+fd22TUnRP67/7N69G/b29njx4gWysrLw/vvvY/LkyYiKioJSqUSNGjU01k9PT0fFihXVr62srFCvXr0Cj/HkyRPExcUhLCwMQ4YMUZdnZmaqa4Sio6PRsGFDjdoRQ507dw729vZQKpXIyMhAx44dsWjRIvX7vr6+cHV1Vb+OiYlBWlqaxnkBwLNnz9T9qy5evIgPP/xQ4/2mTZviwIEDWmO4ePEi0tPT0a5dO4PPIy4uDi9evEDz5s3VZZaWlmjSpAkuXryosW7O34GnpycA4N69e6hcubLBxyeiMkCpBKZNk/oaZWVJZe7uQP368sZVjDFJMiZHR8Db++Xr5fjS1ijTZVtHR/3j+k/btm3xww8/wMrKCl5eXrD4r705LS0N5ubmOH36tLpJSsXe3l79s62t7Us7Z6ueLFu+fDkCAwM13lPt29bW1uBzyK1mzZrYtWsXLCws4OXllacpy87OLk98np6eGv2tVJydnQ2KwZjnowvLHI/hqn4fWaoPPCIibRISgNBQ4I8/ssuCgoC1a6VEibRikmRMY8ZIiyH+62xsSnZ2dnjllVfylDds2BBKpRL37t1Dy5YtC3UMd3d3eHl54d9//0VoaKjWderVq4cVK1bg4cOHWmuTrKysoFQqdTqeajgDXTVq1AgJCQnqIQO0qV27No4fP45+/fqpy44dO5bvPqtXrw5bW1tERkZi8ODBWmMEUOA5VatWDVZWVjh8+DB8/xus7cWLFzh58iRGjx6tw5kREeVj/34pQbp3T3ptZibVJo0fD+T6w5g0MUki1KhRA6GhoejXrx/mzZuHhg0b4v79+4iMjES9evXQUc8xMqZMmYKRI0fCyckJ7du3R3p6Ok6dOoVHjx5hzJgx6N27N2bMmIGuXbti5syZ8PT0xNmzZ+Hl5YWmTZvCz88P8fHxiI6ORqVKleDg4ABra2ujnGtQUBCaNm2Krl27Ys6cOahRowbu3LmDPXv2oFu3bggICMCoUaMwYMAABAQEoHnz5li3bh3Onz+fb8dtGxsbfP755/jss89gZWWF5s2b4/79+zh//jzCwsLg5uYGW1tb7N27F5UqVYKNjU2ezuh2dnYYNmwYxo0bhwoVKqBy5cqYM2cOnj59irCwMKOcOxGVMVlZQHg4MH261PsIALy8gA0bgFat5I2thOAQAAQAWL16Nfr164dPP/0UNWvWRNeuXXHy5EmD+rkMHjwYK1aswOrVq1G3bl20bt0aERER6kfhrays8Ntvv8HNzQ0dOnRA3bp1MWvWLHVzXI8ePdC+fXu0bdsWrq6u2LBhg9HOU6FQ4JdffkGrVq0wcOBA1KhRA7169cL169fh/l+Vc0hICL788kt89tln8Pf3x/Xr1zFs2LAC9/vll1/i008/xaRJk1C7dm2EhITg3n9/tVlYWODbb7/F0qVL4eXlhS5dumjdx6xZs9CjRw/07dsXjRo1QmxsLPbt24fy5csb7fyJqAxRKIDY2OwEqX17aXBIJkg6UwihunqkkpKSAicnJyQnJ8MxVx+g58+fIz4+XmPcHaLSgPc2USmUkiJNTNu/PzBunNTUVooV9P1tCDa3ERERlQYvXgCXLwN16mSXOTpKtUdGmm2grCndKSUREVFZcPMm0KaN1JR2/brme0yQDMYkiYiIqCT73/+ABg2AI0ekSWr79cvuh0SFwiSJiIioJMrIAD79FOjcGXj4UCrz9QXmzNGcZoQMxj5JBmJ/dypteE8TlSDx8UCvXsCJE9ll3boBK1cCfCLWaFiTpCfVaMdPnz6VORIi41Ld0zlH9CaiYmj7dqBhw+wEycoK+PZbYNs2JkhGxpokPZmbm8PZ2Vk9Bk65cuVeOlUHUXEmhMDTp09x7949ODs755mahoiKkYkTpcEhVapWBTZvBvz95YupFGOSZAAPDw8AUCdKRKWBs7Oz+t4momKqcePsn3v2BJYtA3KN4E/GwyTJAAqFAp6ennBzc8OLFy/kDoeo0CwtLVmDRFQSdOkizbnm6wt88AE7aJsYk6RCMDc35xcLERGZxvPn0jxrAwZoJkMzZ8oWUlnDJImIiKi4uXJFak6LiQEyM4EhQ+SOqEzi021ERETFybp1QKNGUoIESM1rqanyxlRGMUkiIiIqDp4+BQYPBvr0AZ48kcpq1wb+/BNwcJA3tjKKzW1ERERyu3BBal47fz67bMAAYNEiwM5OtrDKOtYkERERySkiQnq0X5UglSsHrFkDrF7NBElmrEkiIiKSy3ffASNHZr+uU0caHLJ2bfliIjXWJBEREcnl/fcBHx/p5yFDpKlGmCAVG6xJIiIikkvFisDGjcC1a1LCRMUKa5KIiIiKQmoqMHw4kJCgWd6sGROkYoo1SURERKYWHS09vXb1KnD5MrBvH8AZG4o91iQRERGZihDADz8Ar78uJUgAcPIkcOmSvHGRTmRPkhYvXgw/Pz/Y2NggMDAQJ06cKHD9x48fY/jw4fD09IS1tTVq1KiBX375pVD7JCIiMrrkZCAkBPjoIyA9XSrz9wfOnAFee03e2EgnsiZJmzZtwpgxYxAeHo4zZ86gfv36CA4Oxr1797Sun5GRgTfffBPXrl3D1q1bcfnyZSxfvhze3t4G75OIiMjoTp2SphbZsiW7bORI4PBhoFo1+eIivSiEEEKugwcGBqJx48ZYtGgRACArKws+Pj74+OOPMX78+DzrL1myBHPnzsWlS5dgaWlplH1qk5KSAicnJyQnJ8PR0dHAsyMiojJHCODbb4Fx44AXL6QyZ2dpYMiuXeWMrEww9ve3bDVJGRkZOH36NIKCgrKDMTNDUFAQjh49qnWbXbt2oWnTphg+fDjc3d1Rp04dzJgxA0ql0uB9AkB6ejpSUlI0FiIiIr1FRQGjR2cnSIGBwNmzTJBKKNmSpAcPHkCpVMLd3V2j3N3dHQm5H4/8z7///outW7dCqVTil19+wZdffol58+Zh2rRpBu8TAGbOnAknJyf14qMa2IuIiEgfbdsCYWHSz59+Chw8CPj5yRoSGU72jtv6yMrKgpubG5YtWwZ/f3+EhITgiy++wJIlSwq13wkTJiA5OVm93Lx500gRExFRqaatx8q33wK//QZ8/TVgZVX0MZHRyDZOkouLC8zNzZGYmKhRnpiYCA8PD63beHp6wtLSEuY5xpaoXbs2EhISkJGRYdA+AcDa2hrW1taFOBsiIipzkpKAAQOAPn2kp9hUypUD3nxTtrDIeGSrSbKysoK/vz8iIyPVZVlZWYiMjETTpk21btO8eXPExsYiKytLXXblyhV4enrCysrKoH0SERHp7fBhoEEDYPduac612Fi5IyITkLW5bcyYMVi+fDnWrFmDixcvYtiwYXjy5AkGDhwIAOjXrx8mTJigXn/YsGF4+PAhRo0ahStXrmDPnj2YMWMGhg8frvM+iYiIDJaVBcyaBbRuDdy6JZVZWwN37sgbF5mErNOShISE4P79+5g0aRISEhLQoEED7N27V93x+saNGzAzy87jfHx8sG/fPnzyySeoV68evL29MWrUKHz++ec675OIiMgg9+4B/fpJU4qotG4NrF8PeHnJFxeZjKzjJBVXHCeJiIg0/Pkn0Ls3cPeu9FqhACZOBCZNAiw4DWpxYezvb/5miYiI8qNUAjNmAJMnS01tAODuDqxdC+QYk49KpxI1BAAREVGRSkoCFi3KTpDatQOio5kglRFMkoiIiPLj5ibVGllYAFOnSv2RChhShkoXNrcRERGpKJXAs2eAvX122ZtvSo/4+/rKFxfJgjVJREREgPQYf7t20uCQuZ9pYoJUJjFJIiIi2rcPqF9feopt505pahEq85gkERFR2ZWZCUyYALRvDzx4IJVVqgQEBMgbFxUL7JNERERl082b0thHhw9nl73zDhARAVSsKFtYVHywJomIiMqePXukuddUCZKFBTBvHrBrFxMkUmNNEhERlR1KJfD551JCpOLrC2zaBAQGyhcXFUusSSIiorLDzAy4cSP7ddeuwNmzTJBIKyZJRERUdigUwPLlQO3awMKFwPbtQPnyckdFxRSb24iIqPRKTweuXAHq1s0uc3ICYmIAS0v54qISgTVJRERUOsXFAc2bA23bArduab7HBIl0wCSJiIhKny1bgEaNgNOnpUlqBw6UOyIqgZgkERFR6fH8OfDRR0DPnkBKilRWvTowd668cVGJxD5JRERUOly5IiVHMTHZZe+/DyxZAjg4yBcXlVisSSIiopJv/XrA3z87QbKxkZ5iW7uWCRIZjDVJRERUso0dqzk4ZK1awObNmk+0ERmANUlERFSyNW+e/XP//sCpU0yQyChYk0RERCVbt27SVCO1a0tJEpGRMEkiIqKS48kTYMMGICxMGj1bZdYs+WKiUotJEhERlQz//AO89x5w6RJgbs6xj8jk2CeJiIiKNyGAlSuBxo2lBAkAxo8Hnj6VNy4q9ZgkERFR8ZWaCvTtCwweLA0UCQD16wOHDgHlyskbG5V6TJKIiKh4iokBAgKAdeuyy4YNA44dA2rUkC8uKjOYJBERUfEihDRKdmCgNIo2ADg6Aps2Ad9/Lw0USVQE2HGbiIiKl3nzgHHjsl/7+0sJUrVq8sVEZRJrkoiIqHgZMADw8pJ+HjkSOHyYCRLJgjVJRERUvLi4ABs3Ag8eSANFEsmENUlERCSfR4+AoUOBe/c0y1u2ZIJEsmNNEhERyeP4caBXL+DaNeDGDeCXXwAz/u1OxQfvRiIiKlpCSJ2zW7SQEiQAOHkSiI2VNSyi3JgkERFR0UlKAjp3BsaOBTIzpbJmzYDoaI59RMUOkyQiIioahw8DDRsCu3dnl40fD0RFAT4+soVFlB/2SSIiItPKygLmzAEmTgSUSqnMxQX46SegfXt5YyMqAJMkIiIyrd9/ByZMyH7dqhWwfj3g7S1fTEQ6YHMbERGZVnAw0L8/oFAAX34JREYyQaISgTVJRERkXEJICVFOixcDAwcCrVvLExORAViTRERExpOYCLz1FrB1q2a5nR0TJCpxmCQREZFxREYC9esD+/cDYWHAv//KHRFRoTBJIiKiwlEqgfBw4M03pZokQKo5yj3VCFEJwz5JRERkuDt3gNBQaawjlbfekh7vd3OTLSwiY2BNEhERGWbfPqBBg+wEydwcmDkT+PVXJkhUKrAmiYiI9JOZKT3KP2tWdlmlSsCGDdJ8bESlBGuSiIhIP/fvAytWZL/u2BE4e5YJEpU6TJKIiEg/np7Ajz8ClpbA3LnArl3SNCNEpQyb24iIqGAvXgDp6YC9fXbZ229Lj/hXqiRfXEQmxpokIiLK3/Xr0lxrAwZII2nnxASJSjkmSUREpN2OHdLTa8eOAdu2Ad9/L3dEREWKSRIREWnKyABGjwa6dQMeP5bKqlQBmjSRMyqiIlfoJCklJQU7duzAxYsXjREPERHJ6d9/gebNgYULs8vefVd6eq1xY/niIpKB3klSz549sWjRIgDAs2fPEBAQgJ49e6JevXrYtm2b0QMkIqIisnUr0LAhcOqU9NrKCli8GNi8GXBykjc2IhnonSQdPHgQLVu2BAD8/PPPEELg8ePH+PbbbzFt2jSjB0hERCb24gUwfDjw3ntASopU9sorUl+kjz4CFAp54yOSid5JUnJyMipUqAAA2Lt3L3r06IFy5cqhY8eOuHr1qtEDJCIiE7OwABISsl/37g2cOSPVKhGVYXonST4+Pjh69CiePHmCvXv34q233gIAPHr0CDY2NgYFsXjxYvj5+cHGxgaBgYE4ceJEvutGRERAoVBoLLmPO2DAgDzrtG/f3qDYiKhoKZXSVGAbNkj/KpVyR1QGKBTAypVA7drAsmXAunWAg4PcURHJTu/BJEePHo3Q0FDY29ujcuXKaNOmDQCpGa5u3bp6B7Bp0yaMGTMGS5YsQWBgIBYsWIDg4GBcvnwZbvlMkOjo6IjLly+rXyu0VAW3b98eq1evVr+2trbWOzYiKlrbtwOjRgG3bmWXVaok9SHu3l2+uEqdZ8+AK1eA+vWzy5ydgb//lmqViAiAAUnSRx99hCZNmuDmzZt48803YWYmVUZVrVrVoD5J8+fPx5AhQzBw4EAAwJIlS7Bnzx6sWrUK48eP17qNQqGAh4dHgfu1trZ+6TpEVHxs3y49RJV7vMLbt6XyrVsLTpSUSuDQIeDuXWnWjJYtpUnpSzODzvnSJaBnT2mj6GjA2zv7PSZIRBoMGgIgICAAHTt2xO3bt5GZmQkA6NixI5o3b67XfjIyMnD69GkEBQVlB2RmhqCgIBw9ejTf7dLS0uDr6wsfHx906dIF58+fz7NOVFQU3NzcULNmTQwbNgxJSUl6xUZERUeplGqQcidIQHbZ6NH5N71t3w74+QFt2wLvvy/96+cnlZdWBp3zjz8C/v7AuXPAgwfAkCEmj5PNp1SS6Z0kPX36FGFhYShXrhxee+013LhxAwDw8ccfY9asWXrt68GDB1AqlXB3d9cod3d3R0LOToQ51KxZE6tWrcLOnTuxdu1aZGVloVmzZriVo36+ffv2+PHHHxEZGYnZs2fjzz//xNtvvw1lPv8709PTkZKSorEQkSZTftkdOqTZxJabEMDNm9J6ualqoHJvr6qBKkmJkq7XWO9zfvIEGDgQ6N8fePpUKnvtNeDrr418BnnjzJ3IubkBU6cyWaISQuhp5MiRwt/fXxw6dEjY2dmJuLg4IYQQO3bsEA0aNNBrX7dv3xYAxJEjRzTKx40bJ5o0aaLTPjIyMkS1atXExIkT810nLi5OABD79+/X+n54eLgAkGdJTk7W/WSISrFt24SoVEkIKV2RlkqVpHJjWL9ec9/5LevXa26XmZk3rpyLQiGEj4+0XlHKzBTiwAEp3gMHdDu+rtdY73P+5x8hXn1Vc6WwMCGePDHyWec9H4Ui/zgrVjTe/UOkkpycbNTvb71rknbs2IFFixahRYsWGh2mX3vtNcTFxem1LxcXF5ibmyMxMVGjPDExUef+RJaWlmjYsCFiY2PzXadq1apwcXHJd50JEyYgOTlZvdy8eVP3kyAq5YqipsbT07D1ClMDZSqGNIPpc411PefvvhU4PnQllP6NgQsXpDft7IC1a4EVK6C0LmeymsGCmk9VkpIMu38MrdFksx8ZQu8k6f79+1qfOnvy5InWp8wKYmVlBX9/f0RGRqrLsrKyEBkZiaZNm+q0D6VSiXPnzsGzgE/ZW7duISkpKd91rK2t4ejoqLEQUeH7Cmnbn7YvqpYtpafY8vsIUSgAHx9pvZzu3tXtuLqulx9jNYNt2ZJ3P/peY13PxXLMCAQuHwzz9GcAgMe+9aA8cRpR3qH45BMp4TRVH66XJXIqQuh3/xja96ws9lkjI9G36qlly5bi22+/FUIIYW9vL/79918hhBAjRowQwcHBeldlbdy4UVhbW4uIiAhx4cIFMXToUOHs7CwSEhKEEEL07dtXjB8/Xr3+lClTxL59+0RcXJw4ffq06NWrl7CxsRHnz58XQgiRmpoqxo4dK44ePSri4+PF/v37RaNGjUT16tXF8+fPdYrJ2NV1RMWFvs1ABw7o1gx24MDLj/2y5iRV80zuJhpVmbammX37jBefoXGrvKwZDBDCzCzvfqZM0e0cVL0F9u/Xbf13sVn94gd8KGzwVFSoUHAzHSDFo08zoTa6Np/qe/9oa74r6P4ozHZUMhn7+1vvJOnQoUPC3t5efPjhh8LGxkaMGjVKvPnmm8LOzk6cOnXKoCC+++47UblyZWFlZSWaNGkijh07pn6vdevWon///urXo0ePVq/r7u4uOnToIM6cOaN+/+nTp+Ktt94Srq6uwtLSUvj6+oohQ4aoky5dMEmi0siQfkW6ftlNnJj/F2tmZv6JQO4vKm0x+vhoj3HcuIL7vKj2X5g+Sfp8weqavGhLTHRZKlSQztnbW/dtZuEz0RMb9Y5L1/sj9+9ZlYB/841+xyno/lHt25C+Z7okrq6uQqSnG3Z/UPEje5IkhBCxsbFi8ODBonHjxqJ27doiNDRU/P3330YJqDhgkkQlVX41RYb+NW3IF3/u2qGXfUnl/oLTpbZr7FjdEhBDagpUx1+7VvoC1eULdts2IcqXNywRMcbigGQxBEuNvl9t1zA9XUqCRoyQ/lWdf+7fs7m58RIzQ2s0dd3OxYU1SqVFsUiSSjsmSVQS5VdTtGWLYX+Fb9umX61F7i9WXWp6CvqCy02VvHz8sW778/bW3iSmLQFTlY8eLX1h6nO+jo6mTYBetjTEaXEV1YQARF+sMfr+c94f48blTX5yNyEa43i5EzNDn37Up9mPTW+lg7G/vxVCCKFPHybVuEj5qVy5skF9o4qTlJQUODk5ITk5mZ24qUTIb7RqhSJvWX4OHAD+m2Uo3/3pw9xcvyeI1q+X5lXNOYq06hmR3bul6cTu39d9fzNnAjkH7dc25YmLC/D669Jk9w8e6L7v4kFgOBZjHj6FNTIAALfgjVcQi3QYNo9mQUJCgE2bjL5brRQKqSN/fLx0H0VFSZ2tXybnPQzovp22Y1LJZOzvb72TJDMzswKfYstvwMaShEkSlSRKpfSkji5PExUkZ5JijP3pa/9+IDk5byJjKHNz4OOPgQ4dpARrzZrC77O4cMJjrEQYeiD78awTaIwQbMI1VDHJMfVJuI1FlfSo7snbt7XHkF+C87LtCjqmMeQ3bUxZnEKnqBj7+1vviXrOnj2r8frFixc4e/Ys5s+fj+nTpxc6IKKSoDh9yOn6uPXLqEbIMNb+9NWtG5Caarz9KZXAggXSUpo0xglsQgiq4Jq6bD4+wXjMwgtYmey4RZ0gAUBkZPb/sfnzpSnntBECmDdP+//JhQulWlFdFXa4CJX8Jmvu3VsaAoKTOJcQRmm0E0Ls3r1btG7d2li7kxX7JJGKtj4sph59Wl/6Pm6tbalYMbt/jjH2x8UUS5YYjfkiHZbqwiSUF52w0+THtrGR+9yle1Sf93P+nxw3Tve+U4UZLkJl2zb9zo3DERiP7H2S8hMbG4v69evjyZMnxtidrNjcRoD2vwQrVpRGCs5N1QL9spnqTUGffhf5qVgRSEzUr/8HFa0vMA3T8KX69RE0RS9sxE2U/H6gpqRPXyonJ6kmydbW8OMplYC7u/bPiYKwT5RxGPv7W+8Rt3NPBJucnIxLly5h4sSJqF69eqEDIioO8hs5Ob8PPtWfGvqMHqwLXUZ6ftlo1bpISsqeuiMwEDDT+5OBTG0ZhuIOpDbR2fgMrfEnEyQd6NPZPDkZcHAAPvvM8ONFRemfIAHSZ0hRT6Ejh5I2PYzefZKcnZ3zdNwWQsDHxwcbN240WmBEctFl3iltcn7IFabjp6q/086deZ/oUvVd6NJFs//FN99I/TUK07n27l0pORw6FMjKMjx+Mo37cEMvbIQ90vArOsgdTqmlVAJz50o/z5mj//ZRUYU7vq59oopTv0hd5ddPqzj3x9I7STpw4IDGazMzM7i6uuKVV16BhYXeuyMqEvp8oBS247I+HT9zx3X/PvDJJ9LTONrcvg306JG32c/FBejYUdpXcrJhcf/+O7B6tWHbknFVxAPMxTiMw1wkwUVdfgitZIyqbJk/H5g2DbAyXV94rXSZ7LkkJhv5DSuimtdQjq4KOjFKz6ZShh23Sxd9O1oXtuOyrh0/dRmNuqgWfQZ95GLapQUOilvwEgIQe/C2UEApe0xldRk+XP957AwZpR7QfQqdkjgXnaHTyhhClo7bu3bt0jnp6ty5cyFStuKBHbflYYrq44IGWQQ0/3pRHT8yUvoLUl8KBeDtDUREAPfuZQ+EeO9e3jFSpk8HwsMNPi0qhRTIwgTMxFRMgjmk9s5EuOF1HDPZ2EekO29v4NtvX17bYWjHbQCYMgX44ov8P/deNoZZce38behgoIYw+ve3TpmUQqHTYmZmZpTMTW6sSSp6+tb25Hw0f/9+adE21YSuf70UtlZH9ZddQY8pV6qk/wSlXMrG4oYEsQ9vahRGoq3wwB3ZY+OiuehSU/OyIQBe9jmR3zEMncNOboZOK2MIzt1WBJgkGYcuE5UKoX/18csSGtWHjK4fKFOm6N7cpFov95grxp6/ikvZWdoiUtyBh7pACYWYhMnCDJmyx1YSlqKeOy/nmGIF0Tb3oeqzKTNT+tzRtv+Cms3WrtUtRmMkG8ZUlMkdk6QiwCRJ9wQnP7rWDOnbVp1fQqXtQ2b0aN3+Y1aoUHw/kLmU3sUMmSIc4UKJ7Bv6DjxEG/whe2xyLwqFEOXL67bujz8aPhmzocv+/YX7HDWkj862bUK4uuoWX3GrSVKdb36f3cW5TxIM2SgtLU3s2bNH/PDDD2LhwoUaS2lQ1pOkwo4orU/NkD5/YbzsgyX3ousHii7Lu+++fMRfLlz0Wd7BLo2CfXhTuCJR9riKesn9WaH6nMivpiX34uKSXTuTMyHZssV0D0ZMnFi4z1h9a1Z0+eNQde2MlWwYm+oc8vt9G6vDuexJ0pkzZ4SHh4dwdHQU5ubmwtXVVSgUCmFnZyeqVKlilKDkVpaTpMI+OaHvX0i6tlWvXav7B0vuD1A+ucWleC5Z4kf0EZkwExMwvUw+xTZlSt7PCx+f7KSnoNqHnEt+n025+y6Ghxe8n3r1dIu7sEmSPn109PnjsLg+3aai7Q9w1e/bWGRPklq3bi2GDBkilEqlsLe3F3FxceLGjRuiVatWYltx/u3ooawmScZ4TFPfv5B0Xd/FRffms5zLyJHa/3rhwqWoF21JkB1SRVMclj02uRZVEpBf035+tQ95rq0eNSgFfVHr+vi+rs1txvic1HVdV9finSCpFLYrx8vIniQ5OTmJS5cuqX++cOGCEEKIY8eOiZo1axolKLmV1STJGJ3r9H2KQZ+/Fg1Zvvmm6PsrcOGSe/HGTfEnWoqu2C57LMVp0aXvjCn64hTUV0iXiXQL+8WuTx8dfWrbyfjf33rP0GRpaQmz/yZ2cnNzw40bNwAATk5OuHnzZmFHJCAZ6TpStGo9bXPw6DJaLJC9nrm5NEosoNvcY+bm+s1R5uoqjWuyZo3u26gUZi40IpW38Qui0QCtcAirMAi+uCZ3SEWioHF6FArAx0caO+xluneXpt3Rha6fYebm0ng8vXtL/6piNTcHli0reNtlywo/BlFBn3uq1wsWSOvp+pnq7V24mEg7vZOkhg0b4uTJkwCA1q1bY9KkSVi3bh1Gjx6NOnXqGD1AKjr6JDjbt0uDmrVtC7z/vvSvnx/w4EHBk61q+3Ds3l0a1NHFRfs2OSmV0t9NulJ9cNy7p/s2KpUqSYO7GQuTrrLFAi8wG5/hF3SEC6SRBVPgiAp4KHNkpuPqKk3yfOCA9MeTQvHyJEAXuiYAun6GFaR7d2DbNun/f06VKknlxpo6Q/W5l/vcKlXSHOT2ZRNY65NwkgF0rXLK/K9+8eTJk+KPP/4QQgiRmJgogoODhYODg2jUqJGIjo42SvWW3Mpqc5uuVcCbNxfcuXvcOMOeYtB1DJDRo3XryJizj4KuTYnffKNZBW+s5sApU6SnbeRu3uBSNIsProvDaKpRuAOdRXkkmeyYphyrKzw8e8DWnIO35jeQq4qxOuoW5SPkOY9pyr4z+hynqJ4MKw1k65Pk7u4uPv/8c3H58mWjHLg4K6tJkhAv/8/4ssdqcyZS+n446jscQEGPCOf+4NAl2XF1FSI9XfdrostSsaJmHNu2cSiB0r50wk6RhOxBftJhKUZigQCyTH7sb76R/ogw1j1mjCePjJVslPVEoSieDCsNZEuSpk6dKqpVqybMzMxEixYtxOrVq8WTJ0+MEkRxU5aTJCEK/s+obyKjz4djerr0FFt++8xvgDVdPzh0SXbyGw/K0GlLtD0Fo2uNGZeStVgiXczHaI3COFQRAThRZDHkfCBC13GGci/h4aavPTFUWU8Uiqp2qyST/em2AwcOiH79+gk7Ozvh6OgoBg8eLI4dO2aUYIqLsp4kCZH/f0ZTzcHzsiSkoL8W9fngMNZx9u+XnpgzpPrfkPGeuBT/xQu3xANkD9++BT2EEx4VaQy5n+7SN7kvzoMRqjBRoILIniSppKamiuXLl4vmzZsLhUIhXn31VTFv3jyjBCU3Jkn5M8UcPLqMJmvMvxYNqbEqKG59q/9NPewBF/mWjvifeAZr8REWCWM3r1WoYFhSnjOp+Ppr3Y5V3Ka1INJVsUmSctq9e7eoUKGCMDMzM8buZMckKX/G7kCpy2iy+fUVMpQxE71x44QwN9fcztxcKi9IYfo5cZFvqVRJ6m8XEiKENZ4JO6TmWccDd0xybNVEzIXpk1OUs7ETyUH2cZJUnj59ioiICLRu3RqdO3dGxYoVMX369MI+bFeqaRtXqKTRZ3wPXRw6BNy6VfA69+8DR47oFWaB9B0PKj/btwNff53396hUSuXbt+e/bX6P/1asKC1UfJiZAe+8Iz3Wfu0a8N57wMAWV3EEzbACgwEIjfUTkPc5dNXv1NBhIHx8gC++0O2R8YLoO44ZUZmnb1Z1+PBhERYWJhwdHUW5cuVEv379xJ9//mmUjK24MEVNUmEnjS1ujNWBUo6/bI1Rk2SMKVxU+8ndv0JVNnp0wc2C+iwODoZvW66c6WtoHB0Lfi33krOmRrlug0hRZF/QoVhS4LaqmlBDO/8DeZ/UNLRPjhyP0hMVJdma22bPni1q1aolzMzMRJMmTcTSpUtFSkqKUYIobox9kQs7aWxxZYwOlKbo46RL3IX9oiiquAvzlJKxkpfCfsEXtHh7S/tOT5ceXx8xQvpXdUxdp6MwJOmpVEnqgP/OOy8fY0ihEOIV76dCOWSoxhsXUVPURYzO90HO/zMTJ+oW6+jRhbuHcivrj9JT6SZbkuTi4iJGjx4tzp07Z5QDF2fGvMjGqnEoreT6y7awXxRFVQOmzwzghiZBBb2fXw3Gvn2G13I5OUlf/KrEWlsCpprQePx40yRIuX/H+/YVvE1NXBQxqKtRuAZ9tfZJ0vU+kOMPBJWy/ig9lV6yJUkZGRlGOWBJYMyLLOcHYUkh11+2hfmiKKrfq7GHC1AopNqZtWsLTlJ0aQo2pPN57k74ujzZaOxF2++4oLGr+uBHkQo7dUGmta0YgFVCn6fXtN0Hcjd98VF6Ko2K5dNtpY0xLzKfJtGNXH/ZGvpFUVRfcLreP/ouub+0Db0OujbDaUt4TVVLlrMpTdepM7Q161kiXazEQI3CNN9XRWbMPzoP4fCy+4BNX0TGZewkyUKuDuNlBZ8m0U337kCXLtLTbnfvStejZcvCz7b9MqrZwA3ZbuFC4N13pSeWhMh+z5Cn/PJjqvsi95N7hl6H3L83Nzfp5+++Ax7mmMe1UiXpeuR8AkuXJxsNIQQwZIjm7O752b5d+h3m/P2pvIClxmS0G+0G4b1z38HcoVy+v/ucdLkPVE85jhqleS20XS8iKnoKIfL7L152paSkwMnJCcnJyXB0dCzUvpRKwM8PuH1b+4epQiF9IMbHmz4hIOPbvj3vF5yPj/G+4F52/wDSfaPvcBIHDuiWFCmVhiWuumy3YQPw/vv6xa2PSpWkRDa/34Pq2haUqJXHQxxEK8zB5+i6ra/GvrT97nPS5z4w9DoTkSZjfn8DTJK0MvZFVv21CmivcdB1jBMqnkz9Bfey+2fTJsDVNbsmp39/4M6dwifl2pKAlyUe+oiKAtq2NXx71fn37Cldg/zWye//V+7j2yENryAWMWigsZ67ixLfLzXXuo+cv3s3N6ns3j0mOkRyMfb3t059kpKTk3VeSoOiGieJT5OQrowxka8+/VyKYtiKwk7P4uMjxJYtL+/XlF+foJz9veoiRlxCDZEAtzwjZq9dW/hzJaKiYezvb51qkszMzKDQcahYZUkcRjoXo2ei/2GVOhWGPvdPYZoBX9YMZcwm4oL6BOU+prc3EBGhWVNz6JButVHamhelmiSBoViGhRgFG6QDAHagC7phR4HbElHxZOzvb506bh84cED987Vr1zB+/HgMGDAATZs2BQAcPXoUa9aswcyZMwsdUGlmaOdYIkC/+6cwHeFf1qFaCODmTWm9wt7P+XVczkn199nChUC7dprv3b6t23G0rdeyfgp22g5F52fZbXVn0BBj8bX6uJUqSdeNiMomnZKk1q1bq3+eOnUq5s+fj969e6vLOnfujLp162LZsmXo37+/8aMkIr0ZmpQba247XeVM6HbuBNatk+brUynoSa+c6xUkz3pnzsA8JASdn8Wqi77DCIzDXKTDxqhPKBJRyaX3BLdHjx5FQEBAnvKAgACcOHHCKEERkXzkGLZCldB9842UfB04AKxfL/0bH59/E6Grq277V68nBLBoEdC0KRArJUgZ5ZwwtMJWjMR3SIcNAP0mjSWi0kvvcZJ8fHywfPlyzJkzR6N8xYoV8PHxMVpgRCSPli2lJOFlw1aYqhlKnxowb2891xs0SOrYpNK4Maw2bcIPlavgffYXJKJc9E6SvvnmG/To0QO//vorAgMDAQAnTpzA1atXsW3bNqMHSERFq6gGyjQGVUJXUB8qH58cCd1bb2UnSZ98AsyaBVhZwRzsL0hEeend3NahQwdcuXIFnTp1wsOHD/Hw4UN06tQJV65cQYcOHUwRIxEVMVWH6tw1NcWtGUqV0CkU2QmciqpMI6Hr3RsYN07q/DR/PmBlVdQhE1EJwsEktTDVEABEJU1JGbZC25AHdbwe4sd3NqPh0g/lC4yIilSxGHH70KFDWLp0Kf79919s2bIF3t7e+Omnn1ClShW0aNGi0EHJjUkSUcmTM6Gr+fAoGs7pBcWNG9Ljcqac/4SIig1jf3/r3dy2bds2BAcHw9bWFmfOnEF6ujQAW3JyMmbMmFHogIiIDGFuDrRplYXeN+eg0aiWUoIEAF98Abx4IW9wRFQi6Z0kTZs2DUuWLMHy5cthaWmpLm/evDnOnDlj1OCIiHT24AHwzjvA559nz/jbooVUvZTjs4qISFd6J0mXL19Gq1at8pQ7OTnh8ePHxoiJiEg/hw4BDRoAv/4qvVYopBqkAwek3uZERAbQO0ny8PBAbGxsnvK//voLVatWNUpQREQ6ycoCpk+Xnt9XzT3i6grs2wdMmwZY6D3KCRGRmt5J0pAhQzBq1CgcP34cCoUCd+7cwbp16zB27FgMGzbMFDESEWk3aRIwcaKULAHSbLcxMcCbb8obFxGVCnr/mTV+/HhkZWWhXbt2ePr0KVq1agVra2uMHTsWH3/8sSliJCLSbsQIYMUK4N49IDxcSpiK4xgFRFQiGTxOUkZGBmJjY5GWloZXX30V9vb2xo5NNhwCgKgEiYqShgVv21buSIhIZrIPATBo0CCkpqbCysoKr776Kpo0aQJ7e3s8efIEgwYNKnRARERa3b0L9OkDJCVplrdpwwSJiExC7yRpzZo1ePbsWZ7yZ8+e4ccffzRKUEREGn77DahfXxoYcuBA7TPvEhEZmc59klJSUiCEgBACqampsLGxUb+nVCrxyy+/wM3NzSRBElEZlZkp9TWaOTM7MTp9Wpp/xMdH3tiIqNTTOUlydnaGQqGAQqFAjRo18ryvUCgwZcoUowZHRGXYrVvSdCKHDmWXvf02sGaN9Jg/EZGJ6dzcduDAAURGRkIIga1bt+KPP/5QL3/99Rdu3LiBL774wqAgFi9eDD8/P9jY2CAwMBAnTpzId92IiAh1sqZactZqAYAQApMmTYKnpydsbW0RFBSEq1evGhQbEcngl1+kwSFVCZK5OTBnDrB7NxMkIioyOtcktW7dGgAQHx+PypUrQ6FQGCWATZs2YcyYMViyZAkCAwOxYMECBAcH4/Lly/k23zk6OuLy5cvq17ljmTNnDr799lusWbMGVapUwZdffong4GBcuHAhT0JFRMXIixfSSNlz52aX+fgAmzYBTZvKFxcRlUl6d9z+448/sHXr1jzlW7ZswZo1a/QOYP78+RgyZAgGDhyIV199FUuWLEG5cuWwatWqfLdRKBTw8PBQL+7u7ur3hBBYsGABJk6ciC5duqBevXr48ccfcefOHezYsUPv+IioCO3apZkgde4MREczQSIiWeidJM2cORMuLi55yt3c3DBjxgy99pWRkYHTp08jKCgoOyAzMwQFBeHo0aP5bpeWlgZfX1/4+PigS5cuOH/+vPq9+Ph4JCQkaOzTyckJgYGB+e4zPT0dKSkpGgsRyaB7d6BXL2lC2vnzgR07gAoV5I6KiMoovZOkGzduoEqVKnnKfX19cePGDb329eDBAyiVSo2aIABwd3dHQkKC1m1q1qyJVatWYefOnVi7di2ysrLQrFkz3Lp1CwDU2+mzz5kzZ8LJyUm9+PCpGaKioZpOREWhAJYuBY4cAT75RHpNRCQTvZMkNzc3/P3333nKY2JiULFiRaMEVZCmTZuiX79+aNCgAVq3bo3t27fD1dUVS5cuNXifEyZMQHJysnq5efOmESMmIq3i46VmtF27NMsdHYGAAHliIiLKQe8kqXfv3hg5ciQOHDgApVIJpVKJP/74A6NGjUKvXr302peLiwvMzc2RmJioUZ6YmAgPDw+d9mFpaYmGDRsiNjYWANTb6bNPa2trODo6aixEZELbtwMNGwInTgADBgB61kITERUFvZOkr776CoGBgWjXrh1sbW1ha2uLt956C2+88YbefZKsrKzg7++PyMhIdVlWVhYiIyPRVMeOmkqlEufOnYOnpycAoEqVKvDw8NDYZ0pKCo4fP67zPonIRJ4/Bz7+GOjRA0hOlsoqVMj+mYioGNF5CAAVKysrbNq0CV999RViYmJga2uLunXrwtfX16AAxowZg/79+yMgIABNmjTBggUL8OTJEwwcOBAA0K9fP3h7e2PmzJkAgKlTp+L111/HK6+8gsePH2Pu3Lm4fv06Bg8eDEB68m306NGYNm0aqlevrh4CwMvLC127djUoRiIygthYoGdP4OzZ7LKQEGDZMqmJjYiomNE7SVKpUaOG1pG39RUSEoL79+9j0qRJSEhIQIMGDbB37151x+sbN27AzCy7wuvRo0cYMmQIEhISUL58efj7++PIkSN49dVX1et89tlnePLkCYYOHYrHjx+jRYsW2Lt3L8dIIpLLpk3AkCFAaqr02toaWLgQGDqUnbOJqNhSCPHymSLHjBmDr776CnZ2dhgzZkyB686fP99owcklJSUFTk5OSE5OZv8kosJ49kx6Si3ngxU1agCbN0sT1hIRGZGxv791qkk6e/YsXrx4of45P8YahZuISon796VaJJU+fYAffgDs7eWLiYhIRzrVJJU1rEkiMqIdO4DQUOC774CBA9m8RkQmI0tNEhGRTp4+lQaIzFlT1LUr8O+/QK4BXomIijudkqTu3bvrvMPt27cbHAwRlWDnz0tPr9WvD6xbp1ljxASJiEogncZJyjllh6OjIyIjI3Hq1Cn1+6dPn0ZkZCScnJxMFigRFVNCAKtXA40bAxcuABs2AAVMUE1EVFLoVJO0evVq9c+ff/45evbsiSVLlsDc3ByANKDjRx99xP47RGVNWhrw0UfATz9ll9WtCzRvLl9MRERGonfHbVdXV/z111+oWbOmRvnly5fRrFkzJCUlGTVAObDjNpEO/v5bal67fDm7bOhQYMECwNZWtrCIqOwy9ve33tOSZGZm4tKlS3nKL126hKzcM3oTUekjhDRKdmBgdoJkby81sy1dygSJiEoNvZ9uGzhwIMLCwhAXF4cmTZoAAI4fP45Zs2appxIholLq+XPpMf6NG7PLGjSQBoesXl22sIiITEHvJOnrr7+Gh4cH5s2bh7t37wIAPD09MW7cOHz66adGD5CIihErq+ypRQBg+HDg668BTvlDRKVQoQaTTElJAYBS12+HfZKICpCUBLRpA4SHA+++K3c0RERqsvdJAqR+Sfv378eGDRvUU5HcuXMHaWlphQ6IiIqRx4+B3FMRVawIxMQwQSKiUk/v5rbr16+jffv2uHHjBtLT0/Hmm2/CwcEBs2fPRnp6OpYsWWKKOImoqJ08CYSESKNox8RoDghpZtDfV0REJYren3SjRo1CQEAAHj16BNscT7F069YNkZGRRg2OiGQghPQYf/PmQHw8kJgIjBghd1REREVO75qkQ4cO4ciRI7CystIo9/Pzw+3bt40WGBHJ4OFD6em1Xbuyy15/XeqcTURUxuhdk5SVlQWlUpmn/NatW3BwcDBKUEQkg6NHgYYNNROksWOBgwcBX1/54iIikoneSdJbb72FBQsWqF8rFAqkpaUhPDwcHTp0MGZsRFQUsrKAuXOBVq2AGzeksooVgd27pXJLS3njIyKSid5DANy8eRPt27eHEAJXr15FQEAArl69ChcXFxw8eBBubm6mirXIcAgAKlN69QI2bcp+3aKFNHp2pUryxUREZABjf3/r3SfJx8cHMTEx2LRpE2JiYpCWloawsDCEhoZqdOQmohKiU6fsJGnCBGDqVMBC748GIqJSR6+apBcvXqBWrVrYvXs3ateubcq4ZMWaJCpzPvsMaNcOCA6WOxIiIoPJOpikpaUlnj9/XuiDEpFM7t0DFi/OWz5nDhMkIqJc9O64PXz4cMyePRuZmZmmiIeITOXAAaB+fWnMo5x9kIiISCu9Ox6cPHkSkZGR+O2331C3bl3Y2dlpvL99+3ajBUdERqBUAtOmSX2NsrKkskmTgB492PeIiKgAen9COjs7o0ePHqaIhYiM7e5doE8f4I8/ssuCgoC1a5kgERG9hN6fkqtXrzZFHERkbL//LiVI9+5Jr83MpNqk8eMBc3N5YyMiKgF07pOUlZWF2bNno3nz5mjcuDHGjx+PZ8+emTI2IjJEZiYwcaLUEVuVIHl5SX2SvviCCRIRkY50TpKmT5+O//u//4O9vT28vb2xcOFCDB8+3JSxEZEhJkwApk+XJqoFgPbtgehoaURtIiLSmc7jJFWvXh1jx47FBx98AADYv38/OnbsiGfPnsHMTO+H5Io1jpNEJdqdO0CDBtJktdOnA+PGSU1tRESlnGwjbt+4cUNjbragoCAoFArcuXMHlTh9AVHx4eUlPeJvZQU0by53NEREJZbOf15mZmbCxsZGo8zS0hIvXrwwelBEpKMbN6S51x490ixv25YJEhFRIelckySEwIABA2Btba0ue/78OT788EONsZI4ThJREdm1CxgwQEqQMjKAbdsAhULuqIiISg2dk6T+/fvnKevTp49RgyEiHWRkSI/xf/NNdtnZs0BiIuDhIV9cRESljM5JEsdHIioG4uOBkBDg5Mnssm7dgFWrAGdn2cIiIiqN+MgLUUmxfTvQsGF2gmRlBXz7rdTMxgSJiMjoOC8BUXGXng6MHQssWpRdVrUqsHkz4O8vX1xERKUca5KIiruff9ZMkHr2BM6cYYJERGRiTJKIiruQEOC99wBra+CHH4CNGwEnJ7mjIiIq9ZgkERU3SqXma4UCWL4cOH4c+PBDPuZPRFREmCQRFSeXLwMBAcCePZrlTk5A/fryxEREVEYxSSIqLtaulfoZRUcD/fsDt27JHRERUZnGJIlIbk+fAmFhQN++wJMnUpm7e/bPREQkCyZJRHK6cAFo0kQaDFJl4EDgxAmgZk354iIiIiZJRLKJiJD6H50/L70uVw748UcpYcoxHyIREcmDg0kSFbW0NGD4cCkhUqlbVxocslYt+eIiIiINrEkiKmoPHgA7d2a/HjJEeryfCRIRUbHCJImoqPn5SU1qDg7A+vXAsmWAra3cURERUS5sbiMytZQUwMwMsLfPLuveHWjVCnBxkS8uIiIqEGuSiEzp7Flp7KOPPgKE0HyPCRIRUbHGJInIFIQAvv8eeP11IDYW+OknYM0auaMiIiI9sLmNyNgeP5Y6Y2/dml0WECA1rxERUYnBmiQiYzp5EmjUSDNBGj0a+OsvoGpV2cIiIiL9MUkiMgYhgAULgObNgfh4qczZGdixA/jmG8DaWsbgiIjIEGxuIyqsJ0+A0FDNsY9efx3YuBHw9ZUvLiIiKhTWJBEVlq0tkJGR/XrsWODgQSZIREQlHJMkosIyM5OeXKtXD9i9G5g7F7C0lDsqIiIqJDa3EenrwQPg5k2gYcPsMldXaUwkM/7dQURUWhSLT/TFixfDz88PNjY2CAwMxIkTJ3TabuPGjVAoFOjatatG+YABA6BQKDSW9u3bmyByKnP++gto0ADo2BG4d0/zPSZIRESliuyf6ps2bcKYMWMQHh6OM2fOoH79+ggODsa93F9AuVy7dg1jx45Fy5Yttb7fvn173L17V71s2LDBFOFTWZGVBcycCbRpA9y+Ddy9C3zyidxRERGRCcmeJM2fPx9DhgzBwIED8eqrr2LJkiUoV64cVq1ale82SqUSoaGhmDJlCqrmM/aMtbU1PDw81Ev58uVNdQpU2t27B7z9NvB//wcolVJZmzZS3yMiIiq1ZE2SMjIycPr0aQQFBanLzMzMEBQUhKNHj+a73dSpU+Hm5oawsLB814mKioKbmxtq1qyJYcOGISkpKd9109PTkZKSorEQAQCioqTmtd9+k14rFMCkScD+/YCXl5yRERGRicnacfvBgwdQKpVwd3fXKHd3d8elS5e0bvPXX39h5cqViI6Ozne/7du3R/fu3VGlShXExcXh//7v//D222/j6NGjMDc3z7P+zJkzMWXKlEKdC5UySiUwbRowdarU1AYA7u7A+vXAG2/IGxsRERWJEvV0W2pqKvr27Yvly5fDpYAZ1Hv16qX+uW7duqhXrx6qVauGqKgotGvXLs/6EyZMwJgxY9SvU1JS4OPjY9zgqeQQAujWDfjf/7LL2rUD1q4FPDzki4uIiIqUrEmSi4sLzM3NkZiYqFGemJgIDy1fRnFxcbh27Ro6deqkLsv67698CwsLXL58GdWqVcuzXdWqVeHi4oLY2FitSZK1tTWsOW0EqSgUQI8eUpJkZgZMmQJMmABoqYUkIqLSS9YkycrKCv7+/oiMjFQ/xp+VlYXIyEiMGDEiz/q1atXCuXPnNMomTpyI1NRULFy4MN/an1u3biEpKQmenp5GPwcqpfr3B/75B3jnHaB1a7mjISIiGcje3DZmzBj0798fAQEBaNKkCRYsWIAnT55g4MCBAIB+/frB29sbM2fOhI2NDerUqaOxvbOzMwCoy9PS0jBlyhT06NEDHh4eiIuLw2effYZXXnkFwcHBRXpuVELcvg38/DOQOzHn02tERGWa7ElSSEgI7t+/j0mTJiEhIQENGjTA3r171Z25b9y4ATM9BukzNzfH33//jTVr1uDx48fw8vLCW2+9ha+++opNapTX3r1A377SKNoeHsC778odERERFRMKIYSQO4jiJiUlBU5OTkhOToajo6Pc4ZApvHgBfPklMHt2dlmdOkBMDEfOJiIqoYz9/S17TRJRkbtxA+jdGzhyJLusUydg9WomSEREpMZvBCpb/vc/aWJaVYJkYQHMmwfs3AlUrChvbEREVKywJonKhowM6TH++fOzy3x9gU2bgMBA+eIiIqJiizVJVDZ8+qlmgtStG3D2LBMkIiLKF5MkKhvGj5ea06ysgO++A7ZtAzjpMRERFYDNbVQ2eHsDmzcDTk6Av7/c0RARUQnAmiQqfeLipPGOHj/WLH/jDSZIRESkM9YkUemyeTMweDCQmiq93rJFmouNiIhIT6xJotLh+XNg2DAgJCQ7Qfr7b2kkbSIiIgMwSaKS78oV4PXXgSVLssvefx84fRpwdZUvLiIiKtGYJFHJtm4d0KiRNJ0IANjaAitWAGvXAg4O8sZGREQlGvskUcn09CkwciSwcmV2We3aUp+kOnXki4uIiEoN1iRRybR1q2aCNGAAcPIkEyQiIjIaJklUMvXtC3TvDpQrB6xZI01Oa2cnd1RERFSKsLmNSobMTGkyWhWFQqpJuntXamYjIiIyMtYkUfF37hxQvz6wd69mubMzEyQiIjIZJklUfAkhPanWpAlw4YLUxHb7ttxRERFRGcHmNiqeUlOBDz4ANmzILvP2lgaNJCIiKgKsSaLiJzpammMtZ4L00UfAsWNAtWqyhUVERGULkyQqPoQAfvhBGj376lWpzNFRGvto8WLAxkbe+IiIqExhcxsVD8nJwJAh0oS0Kv7+wKZNrD0iIiJZsCaJioekJGDfvuzXo0YBhw8zQSIiItkwSaLioWpV6Uk2Z2fg55+BBQsAa2u5oyIiojKMzW0kj0ePACsrzVGy33sPaNcOqFBBvriIiIj+w5okKnrHjwMNGwIjRuR9jwkSEREVE0ySqOgIAcybB7RoAVy/DkREAGvXyh0VERGRVmxuo6KRlAQMGADs3p1d1rw50Lq1bCEREREVhDVJZHqHDwMNGmgmSBMmAAcOAD4+soVFRERUENYkkelkZQFz5gATJwJKpVTm4iI1sQUHyxsbERHRSzBJItNITQV69gT27s0ua90aWL8e8PKSLy4iIiIdsbmNTMPOTqpJAgCFAvjyS2D/fiZIRERUYjBJItMwMwN++kl61P+334CpUwELVlwSEVHJwW8tMo6EBODuXSkpUnFzA06flmqSiIiIShjWJFHhRUZKT6916gQ8eKD5HhMkIiIqoZgkkeGUSmDSJODNN4HEROD2bWDcOLmjIiIiMgo2t5Fh7twB3n8f+PPP7LL27aVH/omIiEoB1iSR/vbtA+rXz06QzM2BWbOAPXsAV1d5YyMiIjIS1iSR7jIzpUf5Z83KLqtUCdi4UZpihIiIqBRhkkS6EQLo2FF6nF/lnXekSWorVpQtLCIiIlNhcxvpRqEAQkKkny0sgK+/BnbtYoJERESlFmuSSHcDBwKXLwPdugGvvy53NERERCbFmiTS7to14LvvNMsUCmD2bCZIRERUJrAmifLasUOqNXr8GPDxAbp2lTkgIiKioseaJMqWng6MGiU1pz1+LJVNmyZ12iYiIipjmCSRJC5Oeoz/22+zy957T5pyhFOLEBFRGcQkiYAtW4BGjaTJaAHA2hr4/ntg0ybAyUne2IiIiGTCPkll2fPnwJgxwA8/ZJdVrw5s3ixNWEtERFSGsSapLBs1SjNBev99qTaJCRIRERGTpDJt4kSgQgXAxgZYvhxYuxZwcJA7KiIiomKBzW1lmY+P1LTm5gbUrSt3NERERMUKa5LKiosXpfGOUlI0y9u1Y4JERESkBZOksmDNGiAgANi5Exg6lOMeERER6YBJUmn25AkwYIC0PH0qlZ0/nz1QJBEREeWLSVJp9c8/QOPGUi2SyuDBwPHjQPny8sVFRERUQjBJKm2EAFaulBKkixelMnt7YN066Qm2cuXkjY+IiKiEKBZJ0uLFi+Hn5wcbGxsEBgbixIkTOm23ceNGKBQKdM01AasQApMmTYKnpydsbW0RFBSEq1evmiDyYiY1FejbV6oxev5cKqtfXxr76P335Y2NiIiohJE9Sdq0aRPGjBmD8PBwnDlzBvXr10dwcDDu3btX4HbXrl3D2LFj0bJlyzzvzZkzB99++y2WLFmC48ePw87ODsHBwXiuShxKq82bpRojlWHDgGPHgBo15IuJiIiohFIIIe+jToGBgWjcuDEWLVoEAMjKyoKPjw8+/vhjjB8/Xus2SqUSrVq1wqBBg3Do0CE8fvwYO3bsACDVInl5eeHTTz/F2LFjAQDJyclwd3dHREQEevXq9dKYUlJS4OTkhOTkZDg6OhrnRIuCENJj/lFRUtNaz55yR0RERFRkjP39LWtNUkZGBk6fPo2goCB1mZmZGYKCgnD06NF8t5s6dSrc3NwQFhaW5734+HgkJCRo7NPJyQmBgYH57jM9PR0pKSkaS4nw4oXma4UCWL0aOHOGCRIREVEhyZokPXjwAEqlEu7u7hrl7u7uSEhI0LrNX3/9hZUrV2L58uVa31dtp88+Z86cCScnJ/Xi4+Oj76kUvdOngddeA/bv1yyvUAGoVk2emIiIiEoR2fsk6SM1NRV9+/bF8uXL4eLiYrT9TpgwAcnJyerl5s2bRtu30QkBfPcd0KwZcPUqEBoK3L0rd1RERESljqxzt7m4uMDc3ByJiYka5YmJifDw8MizflxcHK5du4ZOnTqpy7KysgAAFhYWuHz5snq7xMREeHp6auyzQT6z21tbW8Pa2rqwp2N6jx4BYWHAzz9nl/n55W12IyIiokKTtSbJysoK/v7+iIyMVJdlZWUhMjISTZs2zbN+rVq1cO7cOURHR6uXzp07o23btoiOjoaPjw+qVKkCDw8PjX2mpKTg+PHjWvdZYhw/DjRsqJkgffopcOgQULmyfHERERGVUrLWJAHAmDFj0L9/fwQEBKBJkyZYsGABnjx5goEDBwIA+vXrB29vb8ycORM2NjaoU6eOxvbOzs4AoFE+evRoTJs2DdWrV0eVKlXw5ZdfwsvLK894SiWCEMD8+cD48UBmplRWoQIQEQHkqFEjIiIi45I9SQoJCcH9+/cxadIkJCQkoEGDBti7d6+64/WNGzdgZqZfhddnn32GJ0+eYOjQoXj8+DFatGiBvXv3wsbGxhSnYDpJSdK8a7t3Z5c1awZs3AiUhM7lREREJZjs4yQVR8VmnKSrV4FGjYC0NOn1+PHA1KmApaV8MRERERVTpWqcJHqJ6tWBZcsAFxfg11+BmTOZIBERERUR2ZvbKIf79wE7O81JaHv3Bt5+G/iv7xUREREVDdYkFRcHDwINGgCjRuV9jwkSERFRkWOSJDelEpg2DWjbFrhzB1ixAti0Se6oiIiIyjw2t8kpMVEaMTvHmE544w2gdWv5YiIiIiIArEmST2QkUL9+doJkZgZMmQL89hugZbRxIiIiKlqsSSpqSqX0GP9XX0kDRQKApyewfj3Qpo2soREREVE2JklF6fFjoGtX4M8/s8veegv46SfAzU2uqIiIiEgLNrcVJQcHwNxc+tncXBr36NdfmSAREREVQ0ySipK5ObBuHRAQAERFSSNo6znlChERERUNNrcVNQ8P4MQJQKGQOxIiIiIqAKsx5MAEiYiIqNhjkkRERESkBZMkIiIiIi2YJBERERFpwSSJiIiISAsmSURERERaMEkiIiIi0oJJEhEREZEWTJKIiIiItGCSRERERKQFkyQiIiIiLZgkEREREWnBJImIiIhICyZJRERERFpYyB1AcSSEAACkpKTIHAkRERHpSvW9rfoeLywmSVqkpqYCAHx8fGSOhIiIiPSVmpoKJyenQu9HIYyVbpUiWVlZuHPnDhwcHKBQKOQOp0ApKSnw8fHBzZs34ejoKHc4pRavs+nxGpser3HR4HU2vfyusRACqamp8PLygplZ4XsUsSZJCzMzM1SqVEnuMPTi6OjI/4xFgNfZ9HiNTY/XuGjwOpuetmtsjBokFXbcJiIiItKCSRIRERGRFkySSjhra2uEh4fD2tpa7lBKNV5n0+M1Nj1e46LB62x6RXWN2XGbiIiISAvWJBERERFpwSSJiIiISAsmSURERERaMEkiIiIi0oJJUjG0ePFi+Pn5wcbGBoGBgThx4oRO223cuBEKhQJdu3bVKBdCYNKkSfD09IStrS2CgoJw9epVE0Rechj7Gg8YMAAKhUJjad++vQkiL1n0uc4RERF5rqGNjY3GOryX8zL2Nea9nJe+nxePHz/G8OHD4enpCWtra9SoUQO//PJLofZZ2hn7Gk+ePDnPfVyrVi39AxNUrGzcuFFYWVmJVatWifPnz4shQ4YIZ2dnkZiYWOB28fHxwtvbW7Rs2VJ06dJF471Zs2YJJycnsWPHDhETEyM6d+4sqlSpIp49e2bCMym+THGN+/fvL9q3by/u3r2rXh4+fGjCsyj+9L3Oq1evFo6OjhrXMCEhQWMd3suaTHGNeS9r0vcap6eni4CAANGhQwfx119/ifj4eBEVFSWio6MN3mdpZ4prHB4eLl577TWN+/j+/ft6x8YkqZhp0qSJGD58uPq1UqkUXl5eYubMmfluk5mZKZo1ayZWrFgh+vfvr/EFnpWVJTw8PMTcuXPVZY8fPxbW1tZiw4YNJjmH4s7Y11gIobWsrNP3Oq9evVo4OTnluz/ey3kZ+xoLwXs5N32v8Q8//CCqVq0qMjIyjLbP0s4U1zg8PFzUr1+/0LGxua0YycjIwOnTpxEUFKQuMzMzQ1BQEI4ePZrvdlOnToWbmxvCwsLyvBcfH4+EhASNfTo5OSEwMLDAfZZWprjGKlFRUXBzc0PNmjUxbNgwJCUlGTX2ksTQ65yWlgZfX1/4+PigS5cuOH/+vPo93suaTHGNVXgvSwy5xrt27ULTpk0xfPhwuLu7o06dOpgxYwaUSqXB+yzNTHGNVa5evQovLy9UrVoVoaGhuHHjht7xMUkqRh48eAClUgl3d3eNcnd3dyQkJGjd5q+//sLKlSuxfPlyre+rttNnn6WZKa4xALRv3x4//vgjIiMjMXv2bPz55594++238/ynLSsMuc41a9bEqlWrsHPnTqxduxZZWVlo1qwZbt26BYD3cm6muMYA7+WcDLnG//77L7Zu3QqlUolffvkFX375JebNm4dp06YZvM/SzBTXGAACAwMRERGBvXv34ocffkB8fDxatmyJ1NRUveKz0P+UqLhITU1F3759sXz5cri4uMgdTqmk6zXu1auX+ue6deuiXr16qFatGqKiotCuXbuiCLXEa9q0KZo2bap+3axZM9SuXRtLly7FV199JWNkpYcu15j3cuFkZWXBzc0Ny5Ytg7m5Ofz9/XH79m3MnTsX4eHhcodXKuhyjd9++231+vXq1UNgYCB8fX2xefPmAlsEcmOSVIy4uLjA3NwciYmJGuWJiYnw8PDIs35cXByuXbuGTp06qcuysrIAABYWFrh8+bJ6u8TERHh6emrss0GDBiY4i+LNFNe4WrVqebarWrUqXFxcEBsbWya/WPS9ztpYWlqiYcOGiI2NBQDey7mY4hprU5bvZUOusaenJywtLWFubq4uq127NhISEpCRkWGU31tpYoprbGVllWcbZ2dn1KhRo8B7XRs2txUjVlZW8Pf3R2RkpLosKysLkZGRGn/9qdSqVQvnzp1DdHS0euncuTPatm2L6Oho+Pj4oEqVKvDw8NDYZ0pKCo4fP651n6WdKa6xNrdu3UJSUpLGl3lZou911kapVOLcuXPqa8h7WZMprrE2ZfleNuQaN2/eHLGxseo/pgDgypUr8PT0hJWVlVF+b6WJKa6xNmlpaYiLi9P/Pi50128yqo0bNwpra2sREREhLly4IIYOHSqcnZ3Vj+n27dtXjB8/Pt/ttT2ZMmvWLOHs7Cx27twp/v77b9GlS5cy/9i0Ma9xamqqGDt2rDh69KiIj48X+/fvF40aNRLVq1cXz58/N/XpFFv6XucpU6aIffv2ibi4OHH69GnRq1cvYWNjI86fP69eh/eyJmNfY97Leel7jW/cuCEcHBzEiBEjxOXLl8Xu3buFm5ubmDZtms77LGtMcY0//fRTERUVJeLj48Xhw4dFUFCQcHFxEffu3dMrNiZJxdB3330nKleuLKysrESTJk3EsWPH1O+1bt1a9O/fP99ttSVJWVlZ4ssvvxTu7u7C2tpatGvXTly+fNlE0ZcMxrzGT58+FW+99ZZwdXUVlpaWwtfXVwwZMqTMfuDlpM91Hj16tHpdd3d30aFDB3HmzBmN/fFezsuY15j3snb6fl4cOXJEBAYGCmtra1G1alUxffp0kZmZqfM+yyJjX+OQkBDh6ekprKyshLe3twgJCRGxsbF6x6UQQgj96p6IiIiISj/2SSIiIiLSgkkSERERkRZMkoiIiIi0YJJEREREpAWTJCIiIiItmCQRERERacEkiYiIiEgLJklEVGopFArs2LHDpMdo06YNRo8ebdJjEJE8mCQRUaEdPXoU5ubm6Nixo97b+vn5YcGCBcYP6iU6deqE9u3ba33v0KFDUCgU+Pvvv4s4KiIqTpgkEVGhrVy5Eh9//DEOHjyIO3fuyB2OTsLCwvD777/j1q1bed5bvXo1AgICUK9ePRkiI6LigkkSERVKWloaNm3ahGHDhqFjx46IiIjIs87//vc/NG7cGDY2NnBxcUG3bt0ASE1V169fxyeffAKFQgGFQgEAmDx5Mho0aKCxjwULFsDPz0/9+uTJk3jzzTfh4uICJycntG7dGmfOnNE57nfeeQeurq554k1LS8OWLVsQFhaGpKQk9O7dG97e3ihXrhzq1q2LDRs2FLhfbU18zs7OGse5efMmevbsCWdnZ1SoUAFdunTBtWvX1O9HRUWhSZMmsLOzg7OzM5o3b47r16/rfG5EZBxMkoioUDZv3oxatWqhZs2a6NOnD1atWoWcU0Lu2bMH3bp1Q4cOHXD27FlERkaiSZMmAIDt27ejUqVKmDp1Ku7evYu7d+/qfNzU1FT0798ff/31F44dO4bq1aujQ4cOSE1N1Wl7CwsL9OvXDxERERrxbtmyBUqlEr1798bz58/h7++PPXv24J9//sHQoUPRt29fnDhxQuc4c3vx4gWCg4Ph4OCAQ4cO4fDhw7C3t0f79u2RkZGBzMxMdO3aFa1bt8bff/+No0ePYujQoeoEkoiKjoXcARBRybZy5Ur06dMHANC+fXskJyfjzz//RJs2bQAA06dPR69evTBlyhT1NvXr1wcAVKhQAebm5nBwcICHh4dex33jjTc0Xi9btgzOzs74888/8c477+i0j0GDBmHu3Lka8a5evRo9evSAk5MTnJycMHbsWPX6H3/8Mfbt24fNmzerEz19bdq0CVlZWVixYoU68Vm9ejWcnZ0RFRWFgIAAJCcn45133kG1atUAALVr1zboWERUOKxJIiKDXb58GSdOnEDv3r0BSLUzISEhWLlypXqd6OhotGvXzujHTkxMxJAhQ1C9enU4OTnB0dERaWlpuHHjhs77qFWrFpo1a4ZVq1YBAGJjY3Ho0CGEhYUBAJRKJb766ivUrVsXFSpUgL29Pfbt26fXMXKLiYlBbGwsHBwcYG9vD3t7e1SoUAHPnz9HXFwcKlSogAEDBiA4OBidOnXCwoUL9aphIyLjYU0SERls5cqVyMzMhJeXl7pMCAFra2ssWrQITk5OsLW11Xu/ZmZmGk1ggNRMlVP//v2RlJSEhQsXwtfXF9bW1mjatCkyMjL0OlZYWBg+/vhjLF68GKtXr0a1atXQunVrAMDcuXOxcOFCLFiwAHXr1oWdnR1Gjx5d4DEUCkWBsaelpcHf3x/r1q3Ls62rqysAqWZp5MiR2Lt3LzZt2oSJEyfi999/x+uvv67XuRFR4bAmiYgMkpmZiR9//BHz5s1DdHS0eomJiYGXl5e6g3O9evUQGRmZ736srKygVCo1ylxdXZGQkKCRbERHR2usc/jwYYwcORIdOnTAa6+9Bmtrazx48EDv8+jZsyfMzMywfv16/Pjjjxg0aJC6Gezw4cPo0qUL+vTpg/r166Nq1aq4cuVKgftzdXXVqPm5evUqnj59qn7dqFEjXL16FW5ubnjllVc0FicnJ/V6DRs2xIQJE3DkyBHUqVMH69ev1/vciKhwmCQRkUF2796NR48eISwsDHXq1NFYevTooW5yCw8Px4YNGxAeHo6LFy/i3LlzmD17tno/fn5+OHjwIG7fvq1Octq0aYP79+9jzpw5iIuLw+LFi/Hrr79qHL969er46aefcPHiRRw/fhyhoaEG1VrZ29sjJCQEEyZMwN27dzFgwACNY/z+++84cuQILl68iA8++ACJiYkF7u+NN97AokWLcPbsWZw6dQoffvghLC0t1e+HhobCxcUFXbp0waFDhxAfH4+oqCiMHDkSt27dQnx8PCZMmICjR4/i+vXr+O2333D16lX2SyKSAZMkIjLIypUrERQUpFH7odKjRw+cOnUKf//9N9q0aYMtW7Zg165daNCgAd544w2Np8OmTp2Ka9euoVq1aurmptq1a+P777/H4sWLUb9+fZw4cUKjA7Xq+I8ePUKjRo3Qt29fjBw5Em5ubgadS1hYGB49eoTg4GCNpsOJEyeiUaNGCA4ORps2beDh4YGuXbsWuK958+bBx8cHLVu2xPvvv4+xY8eiXLly6vfLlSuHgwcPonLlyujevTtq166NsLAwPH/+HI6OjihXrhwuXbqEHj16oEaNGhg6dCiGDx+ODz74wKBzIyLDKUTuxnMiIiIiYk0SERERkTZMkoiIiIi0YJJEREREpAWTJCIiIiItmCQRERERacEkiYiIiEgLJklEREREWjBJIiIiItKCSRIRERGRFkySiIiIiLRgkkRERESkBZMkIiIiIi3+H0FlpXJcyIA0AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 假设 predictions 和 actual_values 已经定义\n",
    "# predictions 是模型的预测值，actual_values 是真实值\n",
    "\n",
    "\n",
    "length = 1000\n",
    "actual_values = y_true[:length]\n",
    "predictions = y_predict[:length]\n",
    "\n",
    "print(actual_values)\n",
    "print(predictions)\n",
    "\n",
    "# 创建散点图\n",
    "plt.scatter(actual_values, predictions, color='blue', label='Actual vs Predicted')\n",
    "\n",
    "# 添加标签和标题\n",
    "plt.xlabel('Actual Values')\n",
    "plt.ylabel('Predicted Values')\n",
    "plt.title('Actual vs Predicted Values')\n",
    "\n",
    "# 添加对角线，用于比较完美预测的情况\n",
    "plt.plot([min(actual_values), max(actual_values)], [min(actual_values), max(actual_values)], linestyle='--', color='red', linewidth=2, label='Perfect Prediction')\n",
    "\n",
    "# 显示图例\n",
    "plt.legend()\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8491d96550>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length = 50\n",
    "x = [i for i in range(length)]\n",
    "plt.plot(x, predictions[150:150+length], color=\"red\")\n",
    "plt.plot(x, actual_values[150:150+length])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "gru",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
